1. Field of the Invention
This application relates to hearing aids. More specifically, it relates to digital hearing aids comprising means for logging parameters relating to the sound environment and the performance of the hearing aid during use.
2. Prior Art
Modern, digital hearing aids comprise sophisticated and complex signal processing units for processing and amplifying sound according to a prescription aimed at alleviating a hearing loss for a hearing impaired individual. In order to fine-tune the prescription settings, it is beneficial to gather statistical information about sound events from the listening environments in which a particular hearing aid is expected to function. This information may preferably be stored in the hearing aid, and a logging device including a non-volatile storage device is thus included in the hearing aid. In the following, this is denoted a hearing aid log. Parameter values are sampled at log sample intervals, and slowly an image of the daily use of the hearing aid, and the listening environments the user encounters during its use, is built up in the hearing aid log.
In this application, the term “log sample”, unless otherwise noted, is referred to as the measuring and registration of parameter values selected to be recorded in the hearing aid log, over a length of time sufficient to derive at least some form of classification of the prevailing sound environment, e.g. a time interval in the order of minutes. The log sample period, also referred to as the a sound environment sample, is substantially larger than the input sample period, by which the analog voltage representing the sound pressure level is determined in the input A/D converter. State-of-the-art input A/D converters used for sound operate at rate of e.g. 16-96 kHz. The kind of hearing aids discussed in this application are preferably digital hearing aids, where a digital signal processor performs the conditioning and amplification of sounds to the user. This kind of hearing aids usually splits the signal up into a plurality of separate frequency bands using a corresponding plurality of band-pass filters. Each frequency band may then be amplified independently, and compression, noise reduction etc. may be performed on each frequency band.
A hearing aid logging device is described in WO-A1-2007045276. This device essentially logs two kinds of events, the time a user utilizes a specific program in the hearing aid, called usage logging, and a statistic logging of parameters characterizing the sound environment, called histogram logging.
The histogram logging works by accruing counts of events in respective histogram bins, and, whenever a bin is full, increasing the logging interval by a selected factor and reducing the counts in all the histogram bins by the inverse factor, i.e. effectively rebasing the counters and keeping track of the rebasing. This way of logging sound events results in a histogram representing an extended logging period.
Logging data may include, but is not limited to, data characterizing the listening environment, data regarding the user's operation of the hearing aid, i.e. changes in volume settings, changes between different programs in the hearing aid, and data regarding the internal operation of the hearing aid. The logging may also take combinations of different event types, like, the user switching to a particular program in a certain listening situation, into account.
The hearing aid logging device comprises a histogram representing all the possible parameter combinations of sound environments according to a predetermined definition, each parameter combination being represented by a specific bin in the histogram. The sound environment is sampled at specific intervals, and the closest corresponding bin is incremented, recording an occurrence of that particular sound environment in the hearing aid log.
The contents of the log are primarily used in fitting situations, where the hearing aid fitter extracts the data from a memory of the logging device of the hearing aid and interviews the hearing aid user to learn about the user's experience of using the hearing aid with the current settings in particular listening situations during the logging period. When comparing the log data with listening situations recalled by the user, the hearing aid user's memory may fail him or her regarding particular listening situations of short duration, e.g. listening events that may have been logged several weeks ago, and thus long forgotten by the user. This may generate some confusion for the fitter, and may be leading to the fitter altering the settings of the hearing aid unnecessarily. As a result, the hearing aid might be poorly optimized, the adjustments be a waste of time to the fitter, and thus a cause of discomfort to the user.
Instead of recording the sound itself in the hearing aid, a feat that would demand a nearly unlimited amount of memory in the hearing aid in order to store the sound, only a few properties of the sound is stored. Two main criteria determine the properties to be stored, namely measureability and the level of inherent information relevant to settings in the hearing aid.
Experience has shown that a record comprising three parameters strikes an adequate balance between memory economy and level of detail, a first parameter representing the noise level of the sound, a second parameter representing the modulation level of the sound, and a third parameter describing the slope of the noise spectrum in the sound.
The noise level is defined as the background noise level and is measured by averaging a 10% percentile envelope over the sound event sample period. The noise level gives valuable information to the signal processor in the hearing aid regarding the present average level of the noise in the signal, and the noise level may also provide a fitter with information regarding the noise level the user is experiencing during use of the hearing aid.
The modulation level is defined as the amount the useful signal is changing and is determined by measuring a 90% percentile envelope level and subtracting the measured 10% percentile envelope level from the 90% percentile envelope level averaged over the sound event sample period. The modulation level is mainly used by the hearing aid signal processor to determine the presence of speech in the signal, and it may also provide useful information to the fitter regarding the nature of the sound environments experienced by the user of the hearing aid.
The slope of the noise spectrum may be calculated by averaging the 10% percentile envelope level from each frequency band of the plurality of frequency bands and determining the slope of the resulting linear average over the frequency axis. This slope is computed once for each input sample and the result averaged over the sound event sample period. The slope of the noise spectrum allows the hearing aid signal processor to classify the nature of the noise in order to optimize the operation of noise reduction algorithms in the hearing aid for performing maximum noise reduction with minimum audible artefacts, and the fitter may derive useful information from knowledge of this noise spectrum slope in order to determine if certain types of noise are present in the experienced sound environments.
During use, the three parameters are continually measured, and the average levels of the measurements are stored in a buffer. At the sound event sample period the buffer contents are analyzed to classify the sample into a plurality among possible sound environments and a respective bin record in the hearing aid log, incremented, and the buffer reset, in this way, and, over time, a histogram representing the frequencies of the different, possible sound environments is built up in the hearing aid logging device.
The three parameters are collected in a vector representing the averaged sound environment during a predetermined period of time. The vector representing the sound environment is stored as a record for the purpose of subsequent analysis. The plurality of possible sound environments detectable by the system are prearranged as a number of initially empty bins in allocated memory, the collection of bins forming a histogram.
The log may contain one occurrence of one particular listening event, and fifteen occurrences of another, more frequently occurring event. If the hearing aid log, over the course of several weeks, has logged forty-two occurrences of the latter event, but only has allocated room for fifteen counts, the counter in respect of the latter event would have reached a limit and the balance between the different events in the log might become upset, as too much weight would be placed on the single event in relation to the more frequently occurring event. In the following, this is denoted the log overflow problem.
According to the prior art the log overflow problem is solved by decimating the histogram whenever one bin in the histogram reaches the maximum number of counts possible, e.g. fifteen occurrences of a particular sound event. This is done by dividing the contents of all the bins in the histogram by two and halving the sampling rate in order for subsequent samples to normalize the logging data.
However, this way of managing a hearing aid log has at least two undesired implications. The first implication is that particular sound environments logged many times during the initial part of the logging period, and not at all during later parts of the logging period, are kept in the histogram placing substantial weight on those sound environments that may really have lost interest. The second implication is that a strict time limit is imposed on the hearing aid log, either because the lowest possible sample rate is reached after successive decimations, or because the logged data becomes increasingly inaccurate and unreliable due to several occasions of biased logging as described in conjunction with the first implication.